This workshop is designed to introduce the fundamentals and practical applications of modeling data using data mining and machine learning methods. It surveys a series of topics starting from exploratory data analysis, unsupervised learning, supervised learning and other learning methods to uncover the patterns and structure of data targeting practical problem solving and identifying solutions. Students will learn by hands-on programming including such methods as regression, classification, logistic models, non-linear models, tree-based models, association rules, neural network and support vector machines. New developments in learning such as model visualization, deep learning and interpretable machine learning will also be introduced and illustrated.
- Instructor: Karl Ho